摘要：SummaryEnriched tumor epithelium, tumor-associated stroma, and whole tissue were collected by laser microdissection from thin sections across spatially separated levels of ten high-grade serous ovarian carcinomas (HGSOCs) and analyzed by mass spectrometry, reverse phase protein arrays, and RNA sequencing. Unsupervised analyses of protein abundance data revealed independent clustering of an enriched stroma and enriched tumor epithelium, with whole tumor tissue clustering driven by overall tumor “purity.” Comparing these data to previously defined prognostic HGSOC molecular subtypes revealed protein and transcript expression from tumor epithelium correlated with the differentiated subtype, whereas stromal proteins (and transcripts) correlated with the mesenchymal subtype. Protein and transcript abundance in the tumor epithelium and stroma exhibited decreased correlation in samples collected just hundreds of microns apart. These data reveal substantial tumor microenvironment protein heterogeneity that directly bears on prognostic signatures, biomarker discovery, and cancer pathophysiology and underscore the need to enrich cellular subpopulations for expression profiling.Graphical abstractDisplay OmittedHighlights•LMD was used to investigate 3-D molecular heterogeneity in ovarian cancer tissue•Diverse molecular profiles were identified from 3-D spatially separated samples•Molecular heterogeneity impacts HGSOC prognostic sub-type assignment•Proteomic heterogeneity analysis web portal deployed atwww.lmdomics.orgOncology; Cancer systems biology; Proteomics; Transcriptomics
